Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland
This study uses remote sensing data from 2005 to 2023 to analyze the spatiotemporal pattern of agricultural drought severity and hotspots in Somaliland. The Vegetation Condition Index (VCI), derived from MODIS satellite imagery, was employed to assess drought conditions, while CHIRPS rainfall data p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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International Information and Engineering Technology Association
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/114776/ http://psasir.upm.edu.my/id/eprint/114776/1/114776.pdf |
| _version_ | 1848866592433111040 |
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| author | Omar, Abdillahi Osman Alasow, Ahmed Abdiaziz Farah, Abdiweli Ali Shahid, Shamsuddin |
| author_facet | Omar, Abdillahi Osman Alasow, Ahmed Abdiaziz Farah, Abdiweli Ali Shahid, Shamsuddin |
| author_sort | Omar, Abdillahi Osman |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This study uses remote sensing data from 2005 to 2023 to analyze the spatiotemporal pattern of agricultural drought severity and hotspots in Somaliland. The Vegetation Condition Index (VCI), derived from MODIS satellite imagery, was employed to assess drought conditions, while CHIRPS rainfall data provided insights into precipitation patterns. Results revealed significant temporal and spatial variability in drought severity across Somaliland. VCI trends indicated cyclical patterns of vegetation health, with severe stress observed from 2015 to 2018, followed by recovery from 2019 to 2021. A strong positive correlation between VCI and rainfall was observed, with correlation coefficients ranging from 0.5638 in Saaxil to 0.7701 in Togdheer. Drought severity classification identified Sool and Togdheer as the most critically affected regions, with 90% and 85% of their areas under extreme drought conditions, respectively. Saaxil exhibited the lowest percentage of extreme drought at 35%. Temporal analysis of NDVI deviations confirmed prolonged vegetation stress from 2015 to 2018, with notable improvement in 2020 and 2021. The findings underscore Somaliland's vulnerability to recurrent droughts, emphasizing the urgent need for targeted interventions and adaptive management strategies to enhance resilience in this semi-arid region. |
| first_indexed | 2025-11-15T14:23:03Z |
| format | Article |
| id | upm-114776 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:23:03Z |
| publishDate | 2024 |
| publisher | International Information and Engineering Technology Association |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1147762025-01-31T02:35:30Z http://psasir.upm.edu.my/id/eprint/114776/ Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland Omar, Abdillahi Osman Alasow, Ahmed Abdiaziz Farah, Abdiweli Ali Shahid, Shamsuddin This study uses remote sensing data from 2005 to 2023 to analyze the spatiotemporal pattern of agricultural drought severity and hotspots in Somaliland. The Vegetation Condition Index (VCI), derived from MODIS satellite imagery, was employed to assess drought conditions, while CHIRPS rainfall data provided insights into precipitation patterns. Results revealed significant temporal and spatial variability in drought severity across Somaliland. VCI trends indicated cyclical patterns of vegetation health, with severe stress observed from 2015 to 2018, followed by recovery from 2019 to 2021. A strong positive correlation between VCI and rainfall was observed, with correlation coefficients ranging from 0.5638 in Saaxil to 0.7701 in Togdheer. Drought severity classification identified Sool and Togdheer as the most critically affected regions, with 90% and 85% of their areas under extreme drought conditions, respectively. Saaxil exhibited the lowest percentage of extreme drought at 35%. Temporal analysis of NDVI deviations confirmed prolonged vegetation stress from 2015 to 2018, with notable improvement in 2020 and 2021. The findings underscore Somaliland's vulnerability to recurrent droughts, emphasizing the urgent need for targeted interventions and adaptive management strategies to enhance resilience in this semi-arid region. International Information and Engineering Technology Association 2024 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/114776/1/114776.pdf Omar, Abdillahi Osman and Alasow, Ahmed Abdiaziz and Farah, Abdiweli Ali and Shahid, Shamsuddin (2024) Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland. International Journal of Sustainable Development and Planning, 19 (11). pp. 4135-4146. ISSN 1743-7601; eISSN: 1743-761X https://iieta.org/journals/ijsdp/paper/10.18280/ijsdp.191104 10.18280/ijsdp.191104 |
| spellingShingle | Omar, Abdillahi Osman Alasow, Ahmed Abdiaziz Farah, Abdiweli Ali Shahid, Shamsuddin Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland |
| title | Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland |
| title_full | Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland |
| title_fullStr | Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland |
| title_full_unstemmed | Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland |
| title_short | Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland |
| title_sort | spatiotemporal analysis of agricultural drought severity and hotspots in somaliland |
| url | http://psasir.upm.edu.my/id/eprint/114776/ http://psasir.upm.edu.my/id/eprint/114776/ http://psasir.upm.edu.my/id/eprint/114776/ http://psasir.upm.edu.my/id/eprint/114776/1/114776.pdf |